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Record W2062764964 · doi:10.1177/1087057114527127

Identification of Novel Polyphenolic Inhibitors of Shikimate Dehydrogenase (AroE)

2014· article· en· W2062764964 on OpenAlexaff
James Peek, Thomas Shi, Dinesh Christendat

Bibliographic record

VenueSLAS DISCOVERY · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDehydratasePseudomonas putidaBiochemistryPolyphenolShikimate pathwayChemistryDehydrogenaseArabidopsis thalianaShikimic acidEnzymeBiologyAromatic amino acidsAntioxidant

Abstract

fetched live from OpenAlex

Shikimate dehydrogenase (AroE) is an attractive target for herbicides and antimicrobial agents due to its conserved and essential nature in plants, fungi, and bacteria. Here, we have performed an in vitro screen using a collection of more than 5500 compounds and identified 24 novel inhibitors of AroE from Pseudomonas putida The IC50 values for the two most potent inhibitors we identified, epigallocatechin gallate (EGCG) and epicatechin gallate (ECG), were 3.0 ± 0.2 µM and 3.7 ± 0.5 µM, respectively. Based on the high level of structural conservation between AroE orthologs, we predicted that the identified compounds would also inhibit AroE enzymes from other organisms. Consistent with this hypothesis, we found that EGCG and ECG inhibit the AroE domain of the bifunctional dehydroquinate dehydratase-shikimate dehydrogenase (DHQ-SDH) from Arabidopsis thaliana with IC50 values of 2.1 ± 0.3 µM and 2.0 ± 0.2 µM, respectively.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.229
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2014
Admission routes1
Has abstractno

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Same venueSLAS DISCOVERYSame topicPlant tissue culture and regenerationFrench-language works237,207